Munich Personal RePEc Archive
Do institutions and good governance affect inward FDI? Empirical evidence from emerging countries
Younsi, Moheddine and Bechtini, Marwa
Faculty of Economics and Management, University of Sfax, Tunisia
2 July 2019
Online at https://mpra.ub.uni-muenchen.de/94815/
MPRA Paper No. 94815, posted 04 Jul 2019 06:16 UTC
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Do institutions and good governance affect inward FDI? Empirical evidence from emerging countries
Moheddine Younsi a , Marwa Bechtini b
Abstract:
This study seeks to strengthen the existing literature by investigating the relationship between governance indicators and FDI inflows for the emerging countries (ECs) using a dynamic panel gravity model approach over the period 1996~2014. The empirical results reveal that among the six indicators of good governance, political stability, government effectiveness and regulatory quality are found to be robust determinants for FDI attractiveness in Emerging countries. The remaining three indicators, i.e. voice and accountability, rule of law, and control of corruption are found significantly and negatively associated with FDI inflows. The empirical results show also that larger per capita GDP difference between the investing partner and host country, high level of trade openness, low level of inflation rate, and better infrastructure are crucial factors to speed-up FDI inflows in ECs. However, this study provides strong evidence that ECs depict a large gap with regard to the quality of institutions and other macroeconomic factors and thereby their ability to attract FDI. To conclude, policymakers are required to improve the quality of institutions and business climate in order to attract more FDI in these countries.
Keywords: Governance indicators, FDI, Emerging countries, Panel gravity model.
a Unit of Research in Development Economics, Faculty of Economics and Management, University of Sfax, Tunisia.
E-mail address: younsimoheddine@gmail.com
b Unit of Research in Competitiveness, Commercial Decision and Internationalization, Faculty of Economics and Management, University of Sfax, Tunisia.
E-mail address: bechtini.marwa@gmail.com
2 1. Introduction
In a world characterized by an economic activity driven by international trade and capital flows, the foreign direct investment (FDI) attractiveness by both developed and developing countries has become imperative and almost strategic for the economic decision-makers because it contributes to economic development through increasing capital accumulation and production capacity, transferring knowledge, enhancing competitiveness and promoting macroeconomic stability (Borensztein et al., 1998). This is particularly the case for the emerging countries (ECs).
In front of the competition which becoming increasingly intense between countries on the one hand and the unequal distribution of FDIs in the world on the other, each country is first called to build its advantages, adapt to the new economic data based on integration and globalization, and capture the elements of institutional development that permits it to receive more FDI. However, FDI is less determined by fundamental elements such as governance infrastructure, economic freedom, economic and political stability, which are insufficient conditions but necessary. Therefore, the importance of institutional factors for FDI has drawn high attention of academic researchers since the last few years. However, several studies highlighted that countries with sound governance infrastructure are likely to attract more FDI inflows (e.g., Globerman and Shapiro, 2002; Jensen, 2003; Bénassy-Quéré et al., 2007; Busse and Hefeker, 2007; Mengistu and Adhikary, 2011; Morrissey and Udomkerdmongkol, 2012) because private investments cannot be protected in an environment characterized by poor governance (weak protection of property rights, high levels of corruption, or excessive regulation and bureaucracy). Likewise, poor governance serves to bring additional costs to FDI and increases uncertainty (Globerman and Shapiro, 2003; Asiedu, 2006; Cuervo-Cazurra, 2008).
It is well-established that a host country is more attractive for FDI when it has sound policies and regulations, and sound macroeconomic conditions. Starting from this fact, the key policy questions are: what role does institutional quality play in attracting FDI and which institutional factors lead FDI inflows in ECs? Indeed, Dunning (2002) argue that foreign investments have becoming increasingly susceptible to the institutional factors as their motives have shifted from market and resource seeking to more efficiency seeking. Also, Gray and Jarosse (1993) suggest that multinationals want to operate in an environment characterized by reduced uncertainty and transaction costs. This environment is related to the regulation inherent in the legislation governing the activity of multinational companies (MNCs). Such regulation can conceal obstacles that impede the implementation of MNCs and thus cause a diversion effect of FDI flows to countries with more flexible and transparent legislation.
The available literature reveal that though research on FDI and their linkage with institutional factors using different set of countries, data and estimation techniques are voluminous. However, the relationship between institutional quality and FDI flows in the context of ECs is yet not well empirically explored. Therefore, the main objective of this paper is to address this gap and to give empirical evidence of the role of institutional factors in making ECs more attractive to FDI. Specifically, we investigate the importance of good governance for inward FDI in ECs by using a dynamic panel gravity model. We further contribute to the literature by employing a variety of macroeconomic and institutional factors to identify which aspects of macroeconomic and institutional factors affect inward FDI in the ECs.
The rest of the paper is structured as follows. Section 2 discusses the literature review. Section 3 describes the data and the econometric methodology. Section 4 presents the empirical results. Section 5 concludes.
3 2. Literature Review
The relationship between institutional factors and FDI inflows remains debatable in empirical research for a long period and time. For instance, Habib and Zurawicki (2002) found that corruption has a significant negative impact on FDI location. Bénassy-Quéré et al. (2007) look into the role of institutional quality in both 52 host and source countries. Their results revealed that inward FDI is significantly influenced by public efficiency which includes tax system efficiency, easiness to create a business, transparency and lack of corruption, contract law, and security of property rights. Busse and Hefeker (2007) examined the link between political risk, institutions and FDI inflows for a panel of 83 developing countries during the period 1984~2003, and showed that many sub-components of political risk (government stability, quality of bureaucracy, law and order, democratic accountability, corruption and ethnic tensions, and internal and external conflict) have significant impacts on FDI inflows. Similarly, Gani (2007) analyzed the link between good governance and FDI inflows for a group of 70 Asian and Latin American countries over the period 1996~2002.
Mengistu and Adhikary (2011) investigated the effect of good governance on FDI inflows for 15 Asian countries for the period 1996~2007. Their results showed that FDI inflows in Asian countries are significantly influenced by the indicators of good governance. Similarly, Gangi and Abdrazak (2012) examined the impact of good governance on inward FDI for 50 African countries. They found that three out of the six indicators of good governance (voice and accountability, government effectiveness, and rule of law) have significant and positive relationship with FDI. The remaining of dimensions (political stability and absence of violence, regulatory quality and control of corruption) are found statistically insignificant. Bellos and Subasat (2012) investigated the link between corruption and FDI for 24 Latin American countries for the period 1985~2008 by using a panel data gravity model. Further, Subasat and Bellos (2013) examined the impact of institutional factors of FDI for 18 Latin American countries over the period 1985~2008 by using a panel data gravity model. Their empirical results suggest that poor governance enhances FDI not only in the transition countries but also in Latin America.
More recently, Kurul and Yalta (2017) analyzed the effect of governance indicators on FDI inflows for 113 developing countries over the period 2002~2012 by using a dynamic panel approach. They found that voice and accountability, government effectiveness and control of corruption have significant positive influences on FDI inflows. The remaining three dimensions (political stability and absence of violence, regulatory quality, and rule of low) do not significantly affect inward FDI. In the same context, Hossain and Rahman (2017) investigated the relationship between good governance and FDI inflows in 80 developing countries during the period 1998~2014.
Their empirical results reveal that FDI inflows are significantly and positively affected by all good governance indicators.
3. Data and Method 3.1. Data
The sample includes 25 emerging host countries, namely Argentina, Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hong Kong, Greece, India, Indonesia, Malaysia, Mexico, Morocco, Peru, Philippines, Qatar, Romania, Russia, South Africa, Thailand, Tunisia, Turkey, UAE, and Venezuela) and 17 source countries, namely Australia, Austria, Denmark, Finland, France, Germany, Japan, Italy, Luxembourg, Netherlands, Portugal, South Korea , Spain, Sweden, Switzerland, UK, and USA.
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Data on FDI stocks are downloaded from the OECD database. Data on real GDP, per capita GDP, inflation, population aged between 15 and 64, which is used as a proxy of labor force, trade openness, and the number of internet users which is used as a proxy of infrastructure are taken from the World Development Indicators database (http://data.worldbank.org/indicator). In addition, data on production capacity of crude oil, natural gas and other liquids in thousands of barrels are obtained from U.S. Energy Information Administration online database. The data on governance indicators are taken from the Worldwide Governance Indicators project online database (http://data.worldbank.org/govindicators).
3.2. Dynamic Gravity Model Specification
To examine the dynamic effects of institutional factors on FDI for the ECs during the period 1996~2014, we employed the following augmented dynamic panel gravity model:
(1) where FDIis the bilateral FDI stock from country i to country j (current USD), GDPi and GDPj are the GDPs of country i (j), DISTis the geographic distance from the economic center of country i to country j, VAC is voice and accountability, PSTAB is political stability and absence of violence, GOVE is government effectiveness, RQ is regulatory quality, ROL is rule of law, COC is control of corruption, DIFGDPis the difference in per capita GDP between country i and j. LAFis the labor force in the host country. TRADE is the degree of trade openness of country i, INFR is the infrastructure measured by the number of internet users in country i, OILis the production capacity of crude oil, natural gas and other liquids in thousands of barrels of the country i, INF determines the inflation rate of the country i, LANGis the sharing of a common language between the two countries, RELIGis a dummy for countries that sharing a same religion, BORDis the act of sharing a common border, λ is the adjustment parameter, uis the error term.
We estimate Eq. (1) using two-step robust system-GMM estimators (Arellano and Bover, 1995; Blundell and Bond, 1998). The system-GMM is the most commonly used method to capture the endogeneity problems and provides consistent estimates. The soundness of the instruments is conducted by two diagnostic tests. The Hansen (1982) J-test over-identifying restrictions for the validity of GMM instruments variables and the Arellano-Bond AR (1) and AR (2) tests for detect autocorrelation in the level series. However, all the regression results (column 1-6) in Table 1, found there is no autocorrelation problem in the level series applying Arellano- Bond AR (1) and AR (2) process and over identified restriction are valid in the model using Hansen J-test.
4. Empirical Results
The summary statistics of the variables reported in Appendix A1 show that the average inward FDI stocks exhibit a wide variation in the sample period, which indicate a contrasted performance among the ECs in terms of FDI stocks. Regarding the governance indicators, we can observe that there is a large gap between countries with regard to their quality of institutions.
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The empirical results presented in Table 1 have shown good results for the gravity variables as distance and the size of the GDP variables are highly significant and have the expected positive signs. The real GDP of the host countries, which capture the effect of the country’s economic size, has a strong positive effect on FDI inflows in all the models except. For instance, an increase of 1% in real GDP leads significantly to an increase in FDI to ECs by about 0.146% points. This implies that the richer a country the more FDI it attracts. Likewise, the distance variable is significantly and negatively associated with FDI, indicating that an increase in geographical distance or cost of transportation leads significantly to a decrease in FDI.
Regarding the governance indicators, the results show that FDI in ECs is positively and significantly affected by political stability and absence of violence, this implies that a 1% increase in effort to improve political soundness leads to a surge in the FDI to ECs by 0.079% points. This further implies that good political stability that related to political soundness and government ability faces to unconstitutional means including politically motivated violence and terrorism is indeed essential for foreign firms to work effectively. Government effectiveness has a positive and significant impact on FDI, indicating that an increase of 1% in effort to enhance government effectiveness leads to a surge in FDI to ECs by 0.191% points. This implies that good governance effectiveness necessary for well-functioning markets decreases the cost of doing business and therefore boosts FDI activity. Regulatory quality has also a positive and significant effect on FDI, indicating that a 1% increase in effort to improve government regulatory effectiveness leads to a 0.254% points increase in FDI. This provides evidence that improved government regulatory effectiveness serves to create a favorable business climate by hearten foreign investors to undertake long-term investment.
Further, voice and accountability has a negative and statistically significant effect on FDI inflows, revealing that a decrease of 1% in effort to improve democratic accountability leads to a decrease in FDI by -0.239%
points. This implies that poor government that reflects weaknesses in exercising policies to improve the participation and trust of people in political system serves to reduce FDI inflows. Rule of law has also a negative and significant impact on FDI inflows, implying that a 1% decrease in effort to improve transparency and strengthen the rule of law leads to a decrease in FDI inflows by around -0.163% points. This provides a further indication that ECs with weak effective, impartial and transparent legal systems and poor protection of property rights and civil rights tend to attract less FDI. Our results show also that control of corruption has a negative and statistically significant sign, revealing that a 1% decrease in effort to improve the transparency of corruption in ECs leads to a decrease in FDI to ECs by -0.085% points. This gives us evidence that corruption plays a
‘‘grabbing hand’’ role for FDI, and hence high levels of corruption discourage more inward FDI to ECs.
Regarding the pull factors, our results show that larger per capita GDP difference between the investing partner and host country, higher level of trade openness, lower level of inflation rate, the availability and cheap labour costs, and better infrastructure are crucial factors to speed-up inward FDI to ECs. Table 2summarizes our main findings.
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Table 1. Results of dynamic panel system-GMM model Dependent variable : lnFDI
Variables (1) (2) (3) (4) (5) (6)
lnFDIij (t-1) 0.477*** (0.082) 0.475*** (0.084) 0.480*** (0.083) 0.479*** (0.090) 0.479*** (0.084) 0.479*** (0.083) lnGDPi 0.573*** (0.084) 0.568*** (0.075) 0.570*** (0.070) 0.578*** (0.081) 0.573*** (0.069) 0.575*** (0.071) lnGDPj 0.145*** (0.040) 0.144*** (0.038) 0.149*** (0.043) 0.146*** (0.043) 0.148*** (0.038) 0.146*** (0.040) lnDIFGDP 0.363** (0.137) 0.354** (0.124) 0.345** (0.112) 0.368** (0.142) 0.349** (0.135) 0.347** (0.141) lnTRADE 0.405*** (0.128) 0.402*** (0.086) 0.399*** (0.090) 0.386*** (0.118) 0.395*** (0.113) 0.389*** (0.105)
lnOIL 0.013* (0.007) 0.012* (0.005) 0.017* (0.007) 0.011* (0.016) 0.014* (0.022) 0.015* (0.018)
lnINF -0.005** (0.001) -0.006** (0.002) -0.006** (0.001) -0.005** (0.002) -0.007** (0.002) -0.006** (0.002) lnLAF 0.418*** (0.115) 0.396*** (0.124) 0.376*** (0.097) 0.408*** (0.113) 0.389*** (0.081) 0.385*** (0.108) lnINFR 0.112*** (0.017) 0.116*** (0.019) 0.122*** (0.019) 0.118*** (0.019) 0.115*** (0.019) 0.114*** (0.018) lnDIST -0.562** (0.108) -0.564** (0.106) -0.552** (0.124) -0.571** (0.141) -0.569** (0.140) -0.565** (0.136)
LANG 0.728 (0.308) 0.753 (0.263) 0.746 (0.446) 0.758 (0.433) 0.763 (0.412) 0.760 (0.383)
BORD 0.825 (0.270) 0.828 (0.247) 0.835 (0.265) 0.838 (0.235) 0.842 (0.188) 0.845 (0.212)
RELIG 0.798*** (0.185) 0.789*** (0.178) 0.885*** (0.228) 0.880*** (0.224) 0.877*** (0.216) 0.875*** (0.211)
VAC -0.240* (0.130)
PSTAB 0.079*** (0.021)
GOVE 0.191** (0.072)
RQ 0.254** (0.090)
ROL -0.163* (0.041)
COC -0.085* (0.018)
Constant -31.419*** (3.114) -30.155*** (2.288) -28.424*** (2.256) -29.245*** (2.348) -29.491*** (2.795) -29.491*** (2.778)
F-statistic (1976.12)*** (1981.27)*** (1975.22)*** (1976.18)*** (1982.07)*** (1978.12)***
AR (1) test (p-value) 0.002 0.003 0.003 0.003 0.002 0.003
AR (2) test (p-value) 0.314 0.312 0.312 0.312 0.314 0.315
Hansen test (p-value) 0.132 0.128 0.135 0.115 0.132 0.140
N/Group number 6800/425 6800/425 6800/425 6800/425 6800/425 6800/425
Notes: Corrected standard errors in parentheses. ***, **, * represent the 1%, 5%, and 10% significance levels, respectively.
8 5. Conclusions
This study explored the relationship between institutional factors and FDI in ECs for the period 1996~2014 using a dynamic panel gravity model approach. The regression results show that FDI is strongly affected by government effectiveness, political stability and regulatory quality, while voice and accountability, rule of law and control of corruption have significant negative influences on inward FDI. One can be argued that countries that have good governance infrastructure, which secure property rights and civil rights, enforcement status of laws in case of violation of rules and contracts, guarantee the political stability and assurance the transparency and lack of corruption tend to attract more FDI than countries with poor governance. The empirical results also provide evidence that FDI-promoting effect of good governance may be an important channel of their overall influence on growth and development levels. Under this fact, policymakers should take into account that healthy economic and political climate offer an attractive opportunity for foreign investors and they are therefore significant measures that political stability be maintained in ECs which may create a dynamic spillover power in their economies. Furthermore, it should be noted that to encourage FDI to ECs and provide large motivation for foreign investors, a strong commitment by the policy makers is essential to ensure the respect for the rule of law.
Finally, encourage regional integration agreements to harmonize regulatory frameworks and the business climate under which MNCs operate.
Table 2. Summary of main findings
Variables Impact on inward FDI Expected sign Found sign
VAC a significant negative impact + –
PSTAB a significant positive impact + +
GOVE a significant positive impact + +
RQ a significant positive impact + +
ROL a significant negative impact + –
COC a significant negative impact + –
GDPj a significant positive impact + +
DIFGDP a significant positive impact + +
TRADE a significant positive impact + +
OIL a significant positive impact + +
INF a significant negative impact – –
LAF a significant positive impact + +
INFR a significant positive impact + +
DIST a significant negative impact – –
LANG a significant positive impact + +
BORD a significant positive impact + +
RELIG a significant positive impact + +
9 Appendix
Table A1. Description of variables
Variables Description Mean Std. Dev.
FDI Bilateral FDI stock from country i to country j (current USD) 7.845 2.553
GDPi Real GDP of the source country (constant 2005 USD) 27.521 1.350
GDPj Real GDP of the host country (constant 2005 USD) 26.475 1.314
DIFGDP Difference in GDP per capita in thousands USD between the source country
and host country 10.309 0.674
LAF Labour force in the host country, measured by the total population aged
between 15 and 64 17.122 1.540
TRADE The degree of trade openness of the host country, measured by the ratio of
exports plus imports to GDP 3.983 0.656
INFR Infrastructure, measured by the number of internet users in the host country 4.962 2.503 OIL Production capacity of crude oil, natural gas and other liquids in thousands
of barrels of the host country 9.924 2.997
INF Inflation rate in the investing country as a proxy of macroeconomic stability 9.555 16.494 VAC Voice and accountability that measures the extent to which a country's
citizens are able to participate in selecting their government, as well as freedom of expression, association, and a free media.
-0.264 0.657 PSTAB Political stability and the absence of violence to capture the ability
perceptions of the government’s power to the likelihood of political instability and politically motivated violence and terrorism.
0.288 0.831 GOVE Government effectiveness to capture the quality of public service, the
quality of the civil service and the degree of its independence from political pressures, and the credibility of the government’s commitment to such policies.
0.267 0.612 REQ Regulatory quality to capture the ability perceptions of the government to
formulate and implement sound economic policies and regulations that permit and promote private sector development.
0.251 0.671 ROL Rule of law to assess the strength and impartiality of the legal system that
protects property and individual rights. -0.078 0.677
COC Control of corruption that accounts for bribes, excessive patronage and
nepotism. -0.055 0.691
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